Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation.
Development and Validation of a Prognostic Model for Overall Survival in Patients with Primary Pelvis and Spine Osteosarcoma: A Population-Based Study and External Validation.
复制标题
DOI：
10.3390/jcm12072521
复制
发表时间：
2023-03-27
影响因子：
3.9
通讯作者：
Xiao, Jianru
中科院分区：
文献类型：
--
作者：
Wang, Da;Liu, Fanrong;Li, Binbin;Xu, Jinhui;Gong, Haiyi;Yang, Minglei;Wan, Wei;Jiao, Jian;Liu, Yujie;Xiao, Jianru
背景：原发性骨盆和脊柱骨肉瘤（PSOS）是一种治疗困难、预后不良的特殊类型骨肉瘤。近年来对骨肉瘤的研究不断增多，但对PSOS的研究较少；特别是缺乏大样本的分析。本研究旨在构建并验证一个模型来预测 PSOS 患者的总生存期 (OS)，因为目前没有可用于评估其预后的工具。方法：从监测、流行病学和最终结果（SEER）数据库以及长征医院脊柱肿瘤中心收集PSOS患者的人口学信息、临床特征和随访信息等数据。变量选择是通过基于赤池信息准则（AIC）的后向过程实现的。通过单变量和多变量 Cox 分析确定预后因素。进一步构建了列线图来估计 1 年、3 年和 5 年 OS。校准图、一致性指数（C 指数）和接受者操作特征（ROC）用于评估预测模型。结果：SEER数据库和长征医院共收集到83例PSOS患者和90例PSOS患者。在 SEER 队列中，肝转移、肺转移和化疗被认为是 OS 的独立预后因素 (p < 0.05)，并被纳入构建初始列线图。然而，初始列线图在内部和外部验证中显示预测准确性较差。然后，我们把目光转向了长征数据。涉及节段的肺转移、东部肿瘤合作组 (ECOG) 表现评分、碱性磷酸酶 (ALP) 水平和整块切除最终被确定为 OS 的独立预后因素 (p < 0.05)，并进一步纳入构建当前列线图，其中偏倚校正 C 指数为 0.834 (0.824–0.856)。当前列线图的 1 年、3 年和 5 年 OS 概率的 ROC 曲线 (AUC) 下面积分别为 0.93、0.96 和 0.92。结论：我们开发了一种性能良好且具有临床实用性的预测模型，能够有效预测 PSOS 患者的 OS，帮助临床医生做出决策。
Background: Primary pelvis and spine osteosarcoma (PSOS) is a specific type of osteosarcoma that is difficult to treat and has a poor prognosis. In recent years, the research on osteosarcoma has been increasing, but there have been few studies on PSOS; in particular, there have been a lack of analyses with a large sample size. This study aimed to construct and validate a model to predict the overall survival (OS) of PSOS patients, as currently there are no tools available for assessing their prognosis. Methods: Data including demographic information, clinical characteristics, and follow-up information on patients with PSOS were collected from the Surveillance, Epidemiology, and End Results (SEER) database, as well as from the Spine Tumor Center of Changzheng Hospital. Variable selection was achieved through a backward procedure based on the Akaike Information Criterion (AIC). Prognostic factors were identified by univariate and multivariate Cox analysis. A nomogram was further constructed for the estimation of 1-, 3-, and 5-year OS. Calibration plots, the concordance index (C-index), and the receiver operating characteristic (ROC) were used to evaluate the prediction model. Results: In total, 83 PSOS patients and 90 PSOS patients were separately collected from the SEER database and Changzheng Hospital. In the SEER cohort, liver metastasis, lung metastasis, and chemotherapy were recognized as independent prognostic factors for OS (p < 0.05) and were incorporated to construct the initial nomogram. However, the initial nomogram showed poor predictive accuracy in internal and external validation. Then, we shifted our focus to the Changzheng data. Lung metastasis involving segments, Eastern Cooperative Oncology Group (ECOG) performance score, alkaline phosphatase (ALP) level, and en bloc resection were ultimately identified as independent prognostic factors for OS (p < 0.05) and were further incorporated to construct the current nomogram, of which the bias-corrected C-index was 0.834 (0.824–0.856). The areas under the ROC curves (AUCs) of the current nomogram regarding 1-, 3-, and 5-year OS probabilities were 0.93, 0.96, and 0.92, respectively. Conclusion: We have developed a predictive model with satisfactory performance and clinical practicability, enabling effective prediction of the OS of PSOS patients and aiding clinicians in decision-making.
登录
查看更多内容
影响因子：
2.8
作者：
Aoude, A.;Fortin, M.;Jarzem, P.
通讯作者：
Jarzem, P.
影响因子：
19.7
作者：
Ilaslan, H;Sundaram, M;Shives, TC
通讯作者：
Shives, TC
影响因子：
4.2
作者：
Lefebvre, Guillaume;Renaud, Armelle;Cotten, Anne
通讯作者：
Cotten, Anne
影响因子：
45.3
作者：
Ozaki, T;Flege, S;Bielack, SS
通讯作者：
Bielack, SS
影响因子：
3
作者：
Boriani, S;Bandiera, S;Weinstein, JN
通讯作者：
Weinstein, JN